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Query Evaluation Techniques for Multidimensional Data

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Spatial data

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There are two senses of the term “multidimensional data.” The first relates to the data warehousing and online analytical processing (OLAP). The second sense of the term, used mostly in the context of scientific data, refers to variants of array-representable data where the dimensionality refers to the dimensions of the array. Query processing for this class of data uses array algebras [3] and array-specific storage [1] indexing techniques [4].

Key Points

In many scientific applications, data can be represented as multidimensional arrays. For example, the current flow in oceans is a time-varying vector field and can be roughly viewed as 4-dimensional data. In many applications the array may not be uniform, but it can be nested, and even irregular. Query evaluation on this kind of data is greatly dependent on applications. Some applications need to perform operations like value-based clustering on the data, while other applications need fast computation...

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Recommended Reading

  1. Furtado P Baumann P. Storage of multidimensional arrays based on arbitrary tiling. In: Proceedings of the 15th International Conference on Data Engineering; 1999. p. 480–9.

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  2. Howe B, Maier D. Algebraic manipulation of scientific datasets. VLDB J. 2005;14(4):397–416.

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  3. Marathe AP, Salem K. Query processing techniques for arrays. VLDB J. 2002;11(1):68–91.

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  4. Sinha RR, Winslett M. Multi-resolution bitmap indexes for scientific data. ACM Trans Database Syst. 2007;32(3):16.

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Correspondence to Amarnath Gupta .

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Gupta, A. (2018). Query Evaluation Techniques for Multidimensional Data. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1283

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